tamnguyenvan / malnet

Malware Detection using Convolutional Neural Networks

MalNet - Detect malware using Convolutional Neural Networks

By Tam Nguyen Van

Introduction

Malware detection using Convolutional Neural Networks.

Requirements

1. Python >=3
2. Keras (>=2.0.8)
3. Tensorflow (>=1.15)

Installation

1. Clone the repository to your local. git clone https://github.com/tamnguyenvan/malnet
2. Install all requirements (virtualenv is recommneded).

• pip install tensorflow==1.15 (CPU only) or pip install tensorflow-gpu==1.15 (GPU)
• pip install -r requirements.txt

3. Download Ember dataset here. You can go to their home page for more details. Extract to wherever you like.
4. Extract features by running: python create_data.py --data_dir PATH_TO_DATA_DIR. See create_data.py for the details. After that, some .dat file should be created in the same directory.

Training model

Almost done, just run python train.py --data_dir PATH_TO_DATA_DIR for training. Show help to see additional options.

Evaluate model

In case you want to regenerate validation result, run python eval.py --data_dir PATH_TO_DATA_DIR--model_path MODEL_PATH --scaler_path SCALER_PATH. Again, show help to see options.

Deploy

Let's have some fun. We will try the pretrained model on real PE files. Download your PE file then run python test.py --input_file INPUT_FILE --model_path MODEL_PATH.

Contact

Tam Nguyen Van ([e-mail]) Any questions can be left as issues in this repository. You're are welcome all.